Hayaru Shouno

Hayaru Shouno, Eiji Kimura, Kunihiko Fukushima, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

Connected character recognition in cursive handwriting using selective attention model with bend processing

Hayaru Shouno, Kunihiko Fukushima, K. Fukushima, 1994, Systems and Computers in Japan.

Classification of patterns for diffuse lung diseases in thoracic CT images by AdaBoost algorithm

Shoji Kido, Hayaru Shouno, Masayuki Kuwahara, 2009, Medical Imaging.

Improvement of infant's action recognition accuracy by Bayesian estimation method introducing Bayesian Network -- Experimental evaluation with supersonic sensor and camera images

Yoshifumi Nishida, Hayaru Shouno, Yoichi Motomura, 2011 .

Parallel and Distributed Processing Techniques and Applications

Hiroshi Ishii, Georgios Ch. Sirakoulis, George A. Gravvanis, 2015 .

Topographic Analysis of Correlated Components

Aapo Hyvärinen, Michael Gutmann, Hayaru Shouno, 2012, ACML.

The Design and Implementation of Unimodular Transformations for the Parallelizing Compiler PROMIS

Kazuki Joe, Hayaru Shouno, Tomomi Yamaguchi, 2002, PDPTA.

Workshop on Deep Learning and Unsupervised Feature Learning, NIPS

Aapo Hyvärinen, Michael U. Gutmann, Hayaru Shouno, 2011 .

Support Vector Machine Histogram: New Analysis and Architecture Design Method of Deep Convolutional Neural Network

Satoshi Suzuki, Hayaru Shouno, 2017, Neural Processing Letters.

AN EFFECTIVE EVALUATION FUNCTION FOR ICA TO SEPARATE TRAIN NOISE FROM TELLURIC CURRENT DATA

Hayaru Shouno, Mika Koganeyama, Sayuri Sawa, 2003 .

Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations

Aapo Hyvärinen, Michael Gutmann, Hayaru Shouno, 2014, AISTATS.

Recent Studies Around the Neocognitron

Hayaru Shouno, Hayaru Shouno, 2007, ICONIP.

2.スパースモデリングとTopographic ICA

Hayaru Shouno, Hiroaki Sasaki, Hayaru Shouno, 2014 .

A Hierarchical Extension of the HOG Model Implemented in the Convolution-net for Human Detection

Takashi Morie, Hayaru Shouno, Kazuyuki Takahashi, 2012 .

Development of multiple core-level XPS spectra decomposition method based on the Bayesian information criterion

Hayaru Shouno, Hideki Yoshikawa, Kenji Nagata, 2020 .

28pAR-11 Distribution estimation of hyperparameters in two-dimensional Markov random field

Masato Okada, Yoshinori Nakanishi-Ohno, Hayaru Shouno, 2014 .

An Architecture Design Method of Deep Convolutional Neural Network

Satoshi Suzuki, Hayaru Shouno, 2016, ICONIP.

Naive Mean Field Approximation for Sourlas Error Correcting Code

Masato Okada, Masami Takata, Hayaru Shouno, 2006, IEICE Trans. Inf. Syst..

Statistical - mechanical approach for analog neural network model used in image restoration

Masato Okada, Hayaru Shouno, M. Okada, 2001 .

B-DCGAN: Evaluation of Binarized DCGAN for FPGA

Hayaru Shouno, Hideo Terada, 2019, ICONIP.

Computer-Aided Diagnosis of Computational Anatomical Model and Application of Computer-Aided Autopsy Imaging

Rui Xu, Yasushi Hirano, Shoji Kido, 2011 .

Bayesian Image Restoration for Poisson Corrupted Image using a Latent Variational Method with Gaussian MRF pdf

Hayaru Shouno, Hayaru Shouno, 2014, ArXiv.

Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS), JMLR: WCP volume 33

Hayaru Shouno, Michael Gutmann, S. Hiroaki, 2014 .

Dark channel prior based blurred image restoration method using total variation and morphology

Qiang Fu, Fang Ye, Hayaru Shouno, 2015 .

Naive Mean Field Approximation for the Error Correcting Code

Masato Okada, Masami Takata, Kazuki Joe, 2003 .

An Improvement of Program Partitioning Based Genetic Algorithm

Masami Takata, Kazuki Joe, Hayaru Shouno, 2002, PDPTA.

Bayesian Image Restoration for Medical Images Using Radon Transform

Masato Okada, Hayaru Shouno, 2010 .

Interpretation of ResNet by Visualization of Preferred Stimulus in Receptive Fields pdf

Hayaru Shouno, Genta Kobayashi, Hayaru Shouno, 2020, ArXiv.

Analysis of Dropout Learning Regarded as Ensemble Learning

Hayaru Shouno, Kazuyuki Hara, Daisuke Saitoh, 2016, ICANN.

A study on visual interpretation of network in network

Satoshi Suzuki, Hayaru Shouno, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Simultaneous Estimation of Nongaussian Components and Their Correlation Structure

Aapo Hyvärinen, Michael Gutmann, Hayaru Shouno, 2015, Neural Computation.

Analysis of function of rectified linear unit used in deep learning

Hayaru Shouno, Kazuyuki Hara, Daisuke Saitoh, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Formation of a direction map by projection learning using Kohonen's self-organization map

Koji Kurata, Hayaru Shouno, 2001, Biological Cybernetics.

Handwritten Digit Recognition by a Neocognitron with Improved Bend-Extractors

Hayaru Shouno, Kunihiko Fukushima, Eiji Kimura, 1998, ICSC Symposium on Neural Computation.

Analysis of Bidirectional Associative Memory Using SCSNA and Statistical Neurodynamics

Masato Okada, Hayaru Shouno, 2002, PDPTA.

Analysis of Idiopathic interstitial Pneumonia by Self Organization Map on High-Resolution Computed Tomography Images

Shoji Kido, Hayaru Shouno, Yoshiharu Goto, 2007, PDPTA.

Fast Bayesian Restoration of Poisson Corrupted Images with INLA pdf

Hayaru Shouno, Takahiro Kawashima, 2019, ArXiv.

Bayesian Dynamic Mode Decomposition with Variational Matrix Factorization

Hideitsu Hino, Hayaru Shouno, Takahiro Kawashima, 2021, AAAI.

Texture Analysis of Magnetic Domain Images Using Statistics Based on Human Visual Perception

Hayaru Shouno, Ichiro Akai, Ryo Murakami, 2021 .

Deep Feature Compression Using Spatio-Temporal Arrangement Toward Collaborative Intelligent World

Hideaki Kimata, Hayaru Shouno, Motohiro Takagi, 2021, IEEE Transactions on Circuits and Systems for Video Technology.

Knowledge Transferred Fine-Tuning for Anti-Aliased Convolutional Neural Network in Data-Limited Situation

Hideaki Kimata, Hayaru Shouno, Ryuichi Tanida, 2021, ICIP 2021.

Development of spectral decomposition based on Bayesian information criterion with estimation of confidence interval

Yoh-ichi Mototake, Masato Okada, Hideki Yoshikawa, 2020, Science and Technology of Advanced Materials.

Distribution estimation of hyperparameters in Markov random field models

Masato Okada, Yoshinori Nakanishi-Ohno, Hayaru Shouno, 2014 .

Accuracy of the Bethe approximation for hyperparameter estimation in probabilistic image processing

Masato Okada, D. M. Titterington, Hayaru Shouno, 2004 .